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Based on cross-bispectrum, quadratic-nonlinearity coupling between two vibration signals is proposed and used to assess health conditions of rotating shafts in an AH-64D helicopter tail rotor drive train. Vibration data are gathered from two bearings supporting the shaft in an experimental helicopter drive train simulating different shaft conditions, namely, baseline, misalignment, imbalance, and combination of misalignment and imbalance. The proposed metric shows better capabilities in distinguishing different shaft settings than the conventional linear coupling based on cross-power spectrum.

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A new method to estimate the average dielectric constants of cable sections that have undergone aging is proposed. By comparing the experimental Joint Time-Frequency Domain Reflectometry waveform signatures from a new and an aged cable of the same type, it is demonstrated that the change in the average dielectric constant of the insulation material due to aging can be estimated. For example, for a cable containing Cross-Linked Polyethylene insulation, accelerated aging tests based on the modified Arrhenius equation that simulate 120 years of aging at 50 °C operating temperature show that the dielectric constant of the insulation decreases by more than 34.5%. The same tests performed on another cable containing Ethylene-Propylene Rubber insulation show that the average dielectric constant of the insulation decreases by 10.4%. The efficacy of the method is further demonstrated by estimating the increase in the average dielectric constant of a wedge section of a cable that contained water intrusion.

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This paper investigates the sub-synchronous resonance (SSR) phenomenon in a series compensated doubly-fed induction generator (DFIG) based wind farms. A detailed linear state space model of a fixed-series compensated DFIG wind farm is presented for different operating point conditions. The model of the system includes a wind turbine aerodynamics, a 6th order induction generator, a 3rd order two-mass shaft system, a 4th order series compensated transmission line, an 8th order rotor and generator side converter controllers, and 1st order DC link model. The 22nd order system is modeled in Matlab/Simulink, and modal analysis is performed on the modeled DFIG wind farm, and eigenvalues of the system are calculated. The eigenvalue analysis and time-domain simulation results show that SSR can potentially occur in the fixed-series compensated DFIG-based wind farm even at realistic levels of series compensation. The fixed-series capacitor is replaced with a gate-controlled series capacitor (GCSC), which is a series flexible ac transmission system (FACTS) device composed of a pair of gate-commutated switches in parallel with a capacitor that enables one to control impedance and power flow of transmission lines, for series compensation and SSR damping. The root-locus analysis is employed to design a SSR damping controller (SSRDC) for the GCSC. It is shown than a well-designed SSRDC for the GCSC can alleviate the SSR in DFIG-based wind farms. The IEEE first benchmark model adapted with a DFIG-based wind farm is employed as a case study.

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Wind energy is an important contributor to the evolution of the smart grid, but the power electronics necessary to interface a wind turbine generator (WTG) to the grid can have a negative impact on the power quality (PQ) of the grid if the effects are not well understood. In this paper, the wind energy conversion system is reviewed with models of the two most common types of WTGs: a doubly-fed induction generator (DFIG) and a synchronous generator (SG). Time-frequency analysis is introduced as a unique, advantageous way of quantifying and comparing the time-varying disturbances introduced by these generators, which can not be accomplished from the existing PQ indices published by International Electrotechnical Commission (IEC). Time-frequency distributions and metrics are employed to analyze the PQ effects of the DFIG and SG under two case studies: a three-phase-to-ground fault and a generator trip and recovery. The analysis of these studies reveals time-varying frequency information that can be used to properly compensate for such events in the future depending upon the type of generator employed and improve the quality of power these types of WTGs inject onto the grid.

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This paper presents a novel ultrasonic guided wave based inspection
methodology for detecting and evaluating gas accumulation in nuclear
cooling pipe system. The sensing is in-situ by means of low-profile
permanently installed piezoelectric wafer sensors to excite
interrogating guided waves and to receive the propagating waves in the
pipe structure. Detection and evaluation is established through advanced
cross time-frequency analysis to extract the phase change in the sensed
signal when the gas is accumulating. A correlation between the phase
change and the gas amount has been established to provide regulatory
prediction capability based on measured sensory data.

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In order to properly suppress the harmonic current in a power system, the harmonic similarity metric is developed in this paper and used to establish an efficient strategy for harmonic filter placement. To validate the strategy, an industrial distribution system is analyzed under two harmonic current injection scenar- ios. It is demonstrated that the proposed strategy has a robust ability to successfully determine the most efficient and effective location for placing a harmonic filter bank based upon the desired objectives. The two harmonic current injection scenarios serve to validate the proposed strategy regardless of the power distribution level at which harmonic current is injected. Index Terms—Filtering, harmonic similarity (HS), industrial distribution system, power quality, power-system harmonics.

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This paper introduces a quadratic-nonlinearity powers-index spectrum (QNLPI(ƒ)) measure that describes quantitatively how much of the mean square power at certain frequency ƒ is generated by nonlinear quadratic interaction between different frequencies inside signal spectrum. The proposed index QNLPI(ƒ) is based on the bicoherence spectrum, and the index can be simply seen as summary of the information contained in the bicoherence spectrum in two dimensional graph which makes it easier to interpret. The proposed index is studied first using computer generated data and then applied to real-world vibration data from a helicopter drive train to characterize different mechanical faults. This work advances the development of health indicators based on higher order statistics to assess fault conditions in mechanical systems.

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For efficient maintenance of a diverse fleet of aging air- and rotorcraft, effective condition based maintenance (CBM) must be established based on rotating components monitored vibration signals. Traditional linear spectral analysis techniques of the vibration signals, based on auto-power spectrum, are used as common tools of rotating components diagnoses. Unfortunately, linear spectral analysis techniques are of limited value when various spectral components interact with one another due to nonlinear or parametric process. In such a case, higher order spectral (HOS) techniques are recommended to accurately and completely characterize the vibration signals. Since the nonlinearities result in new spectral components being formed with coherency in phase, the detection of such phase coherence may be carried out with the aid of higher order spectra. In this paper, we use the bispectrum as a higher order spectral analysis tool to investigate nonlinear wave-wave interaction in vibration signals. Accelerometer data has been collected from baseline tests of accelerated conditioning in tail rotor drive-train components of an AH-64 helicopter drive-train research test bed simulating drive-train conditions. Through bispectrum analysis, we compare the harmonics interaction patterns contained in vibration signals from different physical setting of helicopter drive train and compare that with classical power spectral density plots. The analysis advances the development of higher order statistics and two dimensional frequency health indicators in order to qualify health conditions in mechanical systems.

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In this paper, we present a time-frequency based reflectometry solution that focuses on the practical implementation of in-situ and non-destructive cable diagnostic tests. Towards this ideal health monitoring approach, we have explored the implementation of alternative monitoring techniques using surface wave injection for monitoring of cable insulation health toward nondestructive tests. Through use of surface wave propagation, a diagnostic signal can be injected in control, instrumentation, and power cable without removing installed samples under test. However, in practical implementation of surface wave tests through antenna, problems are presented in the form of dispersive media distorting the response of the frequency sweeping reference signal in either frequency or time-frequency domains. We present an optimal reference signal and time-frequency cross correlation diagnostic and prognostic algorithm to allow for implementation of joint time-frequency domain reflectometry (JTFDR) in minimal bandwidth to reduce attenuation in surface wave reflectometry.

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A new concept of nonparametric signal detection and classification technique is proposed using mutual infor- mation measures in the time-frequency domain. The time- frequency-based self-information and mutual information are defined in terms of the cross time-frequency distribution. Based on time-frequency mutual information theory, this paper presents applications of the proposed technique to real-world vibration data obtained from a dedicated condition-based-maintenance experimental test bed. Baseline, unbalanced, and misaligned experimental settings of helicopter drivetrain bearings and shafts are quantitatively distinguished by the proposed techniques. With imbalance quantifiable by variance in the in-phase mutual infor- mation and misalignment quantifiable by variance in the quadra- ture mutual information developed and presented herein, machine health classification can be accomplished by use of statistical bounding regions.

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Accelerometer data has been gathered from accelerated conditioning in grease lubricated and lubrication deprived gear meshes in AH-64 helicopter intermediate and tail rotor gearbox, which are commonly problematic components of the Apache helicopter platform. These tests were performed in a controlled drive-train research test bed, simulating drive-train conditions to improve diagnostic and prognostic capabilities of Condition Based Maintenance (CBM) practices in Integrated Vehicle Health Monitoring System - Health Usage Monitoring System (IVHMS-HUMS) and other comparable CBM packages, as monitored by a standardized Digital Source Collector (DSC) system. Time-frequency representations of vibration measurement collected from two spaced sensors are used to provide signature analysis of transient system harmonics. Furthermore, the time-frequency mutual information advanced signal processing technique is then proposed and validated using vibration data. The measure advances the development of mutual information health indicators to quantify degradation of the helicopter power train. The AH-64 test systems perform under stress in realistic loading conditions and lifetime accelerated aircraft aging is monitored using the proposed advanced signal processing techniques for baseline tests for comparison with faulted conditions.

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Utilities are experiencing premature failures of power cables. In order to prevent electrical outages and to save on repair expenses, a nondestructive and nonintrusive condition assessment technique is highly desirable to evaluate the cable status and to predict the remaining life of a cable. In this paper, the capability of joint time-frequency domain reflectometry (JTFDR) as such a condition assessment technique is studied. The health status of three popular insulations in power system cables - cross-linked polyethylene, ethylene propylene rubber, and silicone rubber - is monitored using the JTFDR in a thermal accelerated aging test. The experimental results show that the JTFDR can successfully monitor the aging process of all three insulations. Then, the results from the JTFDR are compared with the results from the elongation at break (EAB); the results show that the JTFDR technique is comparable with the EAB and has a great potential as a nondestructive and nonintrusive condition assessment technique.

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Recently, VTB has been developed as a naval electric ship evaluation program. However, the behind-the-source modeling level of the system generators is still not enough to realize the actual system. Especially, the results of harmonic analysis and fault analysis were not reliable because the ideal voltage source was used as a generation system due to the lack of a detailed model. For this reason, a more accurate generation model is needed to analyze the dynamic characteristics of the generation system. The work of this paper is featured by the applications of VTB for generation system modeling and simulation methods for electric ship power system design.

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A new methodology for the evaluation of nonfailure operating time (NFOT) in the virtual test bed (VTB) environment is proposed. The proposed method is featured by the application of time-frequency analysis to estimate the parameters of reliability at the earliest stages of design based on the intercoupling of the 1/ f noise and the reliability of power system elements. The proposed approach enables one to directly quantify the reliability of the system by the investigation of the physical properties of the nonequilibrium fluctuations.

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In this paper, we propose a high-resolution time-frequency-domain reflectometry technique as a methodology of detection and estimation of faults on a wire. This method adopts the time-frequency cross-correlation characteristics of the observed signal in both the time and frequency domains simultaneously. The accuracy of the proposed method is verified with experiments using a radio-guide-type coaxial cable and comparing it with traditional time-domain as well as frequency-domain reflectometry methods. It is clearly shown here that the proposed algorithm produces excellent results compared to the conventional methods for single as well as multiple fault cables.

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In this paper, we present a multiple mode sensing methodology to detect active corrosion in aluminum structure utilizing the broadband piezoelectric wafer active sensors. This method uses ultrasonic Lamb wave complemented with the electro-mechanical impedance measurement to detect, quantify, and localize the corrosion progression in plate-like structures. The ultimate objective of this research is to develop in-situ multi-mode sensing system for the monitoring and prediction of critical aerospace structures that can be used during in-service period, recording and monitoring the changes over time. The test experiments were conducted on an aluminum plate installed with a five sensor network using 7-mm piezoelectric wafer active sensors. The corrosion was emulated as material loss of an area of 50mm 38mm on the other surface of the plate. Detection of corrosion and its growth was first conducted using the Lamb wave method in pitch-catch mode. The corroded area resulted in a thickness loss on the Lamb wave propagation and caused the amplitude and phase changes in the structural responses. The experimental data was first evaluated by the statistics-based damage indicator using root mean square deviation. Though the damage indicator is able to detect the presence of the corrosion and identify the corrosion location quantitatively, it failed in giving the right indication of corrosion development. A more corrosion signal processing based method, the cross time-frequency analysis, was proposed and used to analyze the phase characteristics of the data set. This cross time-frequency analysis was found more reliable and precise for detecting the corrosion progression compared with the damage indicator method.

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This paper develops a signal processing, time-frequency analysis-based analytic solution to locate transient capacitor switching disturbances. The flow of transient disturbance energy caused by the capacitor switching is determined by the time and frequency localized phase difference. Cross time-frequency analysis provides time- and frequency-localized phase difference between the transient voltage and current disturbance waveforms which determine the direction of transient disturbance energy flow. The time and frequency localization properties of the proposed scheme allows one to expand the application to complicated power distribution systems without knowledge of system parameters, capacitor size, and configuration. The proposed scheme has been verified by the electromagnetic transients program simulation for all possible spatial locations of the capacitor switching.